Social network analysis of B2B networks
The volume of information readily available in the EMarketplace is massive.Business-to-business (B2B) users, for instance, have an extensive chain of business relationships that have immensely generated a large volume of information. Although this raises problems of information overload, the data is...
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my.uum.repo.228572017-07-27T02:03:00Z http://repo.uum.edu.my/22857/ Social network analysis of B2B networks Mohamad, Abdul Hadi Fang, Wang Abu Bakar, Noor Widasuria Jatavallabhula, Pavan Kumar QA75 Electronic computers. Computer science The volume of information readily available in the EMarketplace is massive.Business-to-business (B2B) users, for instance, have an extensive chain of business relationships that have immensely generated a large volume of information. Although this raises problems of information overload, the data is embedded with rich and valuable information, such as internal structure and social networks.While other research focuses on discovering properties of B2C, C2C and P2P networks, there only exists limited work on B2B, attributable to the high complexity of the B2B structure.This paper presents a statistical analysis of B2B networks that amasses dispersed users' social relationships using a social network analysis technique.The investigation performed found that B2B networks are small-world, and thus follow a power-law distribution. The analysis also proved that B2B networks hold stable community structures. 2017-04-25 Conference or Workshop Item PeerReviewed application/pdf en http://repo.uum.edu.my/22857/1/ICOCI%202017%20341-349.pdf Mohamad, Abdul Hadi and Fang, Wang and Abu Bakar, Noor Widasuria and Jatavallabhula, Pavan Kumar (2017) Social network analysis of B2B networks. In: 6th International Conference on Computing & Informatics (ICOCI2017), 25 - 27 April 2017, Kuala Lumpur. http://icoci.cms.net.my/PROCEEDINGS/2017/Pdf_Version_Chap06e/PID151-341-349e.pdf |
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QA75 Electronic computers. Computer science Mohamad, Abdul Hadi Fang, Wang Abu Bakar, Noor Widasuria Jatavallabhula, Pavan Kumar Social network analysis of B2B networks |
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The volume of information readily available in the EMarketplace is massive.Business-to-business (B2B) users, for instance, have an extensive chain of business relationships that have immensely generated a large volume of information. Although this raises problems of information overload, the data is embedded with rich and valuable information, such as internal structure and social networks.While other research focuses on discovering properties of B2C, C2C and P2P networks, there only exists limited work on B2B, attributable to the high complexity of the B2B structure.This paper presents a statistical analysis of B2B networks that amasses dispersed users' social relationships using a social network
analysis technique.The investigation performed found that B2B networks are small-world, and thus follow a power-law distribution. The analysis also
proved that B2B networks hold stable community structures. |
format |
Conference or Workshop Item |
author |
Mohamad, Abdul Hadi Fang, Wang Abu Bakar, Noor Widasuria Jatavallabhula, Pavan Kumar |
author_facet |
Mohamad, Abdul Hadi Fang, Wang Abu Bakar, Noor Widasuria Jatavallabhula, Pavan Kumar |
author_sort |
Mohamad, Abdul Hadi |
title |
Social network analysis of B2B networks |
title_short |
Social network analysis of B2B networks |
title_full |
Social network analysis of B2B networks |
title_fullStr |
Social network analysis of B2B networks |
title_full_unstemmed |
Social network analysis of B2B networks |
title_sort |
social network analysis of b2b networks |
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2017 |
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http://repo.uum.edu.my/22857/1/ICOCI%202017%20341-349.pdf http://repo.uum.edu.my/22857/ http://icoci.cms.net.my/PROCEEDINGS/2017/Pdf_Version_Chap06e/PID151-341-349e.pdf |
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